The use of investor dollars by technology-based entrants to subsidise the costs of rapidly scaling up a customer base and winning market share is not a new strategy. The experience of the taxi industry follows a familiar pattern already seen in the airlines, music, book, retailing and finance industries that had been disrupted by online access, dynamic pricing and on-demand matching. Effectively, the impact of ridesharing on the taxi industry is a broad reflection of how information disrupts traditional businesses built on the ownership of physical assets.

In this context, the traditional taxi industry is built on the regulation of the supply of taxis and fares. The fixed supply and fares can be viewed as a social bargain to achieve a reasonably stable supply of taxi services and fares to the public while ensuring decent income for the taxi drivers and returns for license owners. Prior to the disruption, capital owners were able to extract rents because of rules that made unofficial sharing (private and part-time taxis) illegal.

Disruption occurs when improved information capabilities transform a vertically integrated industry into a network. The new information efficiencies disrupt status quo by making apparent the inefficiencies of segmentation and price regulation. For example, traditional regulation results in a substantial level of unmatched needs and unutilised (taxi) capacity as reflected by taxis queuing for passengers and vice-versa. Ridesharing utilises information to reduce matching inefficiencies and to reduce the lengths of queues.

Bill Gurley notes the price of taxi rides “only go up, they never go down. How could one possibly know if this is the appropriate supply of taxis and an optimal price point? Doesn’t the high-value of medallions implicitly prove that the market is undersupplied and that prices are above true market clearing prices? What if someone could run a more convenient, safer service at a much lower price and with much higher availability? You would end up with dramatically more rides – and that is exactly what is happening.”

But it is not only information disruption that is placing tremendous stress on regulation. Traditional regulation is failing under its own weight. This is because the relevance of regulated fares decays as the gaps between fares, costs, returns, affordability and service coverage widen over time. Worsening traffic congestion (crowding) increases the extremes in supply and demand slack. As congestion reduce pick-up times and lower taxi utilisation, this will reduce the driver’s paying ride per hour and fares would need to rise for taxi drivers to maintain their incomes.

Higher fares and traffic congestion will also weaken geographical coverage. Taxi drivers will tend to congregate at the most profitable routes while coverage of marginal routes will worsen as income falls and illegal operators proliferate. Deteriorating pick-up times, uneven coverage and upward pressure on rates will increase dissatisfaction with regulated taxi services.

The looming breakdown of traditional regulation is perhaps making policy-makers more inclined to accommodate the disruptive practices of new entrants. Aswath Damodaran observes “even hardliners in the taxicab and old-time car service businesses recognize that ridesharing is not going away and that the ways of doing business have to change…If you own a taxi cab or a car service business, the question is no longer whether you will lose business to ridesharing companies but how quickly, even with the regulatory authorities standing in as your defenders.”

The infusion of information content into the business is giving rise to an air of inevitability on the demise of the traditional model. The traditional model has low information content. Matching is random – depending on the outcome of a queue or hailing. Customers do not have the ability to exercise their choice of driver or car – or have limited ability to plan their trip.

In contrast, ridesharing platforms address taxi logistical problems by organising information from a community of drivers, cars and customers. Information-based models reduce supply rigidities by tapping part-time drivers and vehicles to augment supply. Auction pricing is used to incentivise expansion of supply when demand rises. Profiling and ratings are used to build trust and reputation.

The disruption of the taxi (and other) industry is part of the broader experience of the transition to an information society. In this regard, the traditional taxi model aims to achieve stability and requires a full-time commitment to capital investments in cars, employment of drivers and the provision of service coverage. In contrast, price volatility and constant change is a major aspect of the transition. Ridesharing platforms take advantage of their lack of permanent commitments, their business models are fluid and they seek every opportunity to arbitrage costs and regulations.

This means the transport coverage, costs and income opportunities provided by ridesharing platforms are transient and unstable. If investors are unable to tolerate further losses in funding the investments in technology and competitive fares or if regulators decide to intervene, the ridesharing platforms may react by rationalising routes, raising fares or reducing pay-outs to drivers to the detriment of the long-term interest of customers, drivers and regulators.

Hubert Horan points out that “in mid-2015, after hundreds of thousands of drivers were locked in to vehicle financial obligations, Uber eliminated driver incentive programs and reduced the standard driver share of passenger fares from 80 to 70 percent… eliminated much (if not all) of the economic incentive that got drivers to switch to Uber in the first place.”

On the flip side, technology opens up many exciting opportunities to re-conceptualise the taxi business without being bounded by legacy, time and geography. The new technology-based entrants can explore opportunities in logistics, carpooling, car rentals, leasing partnerships, concierge services, tourism and travel-related opportunities, food recommendations and deliveries.

In theory, these opportunities are also open to traditional taxi companies who could leverage off their core business to venture into partnerships and cross-selling in related areas. But the evidence, from industries such as retailing and media, is that physical-based incumbents struggle to change their business model due to legacy costs and the cultural and mindset resistance to technology and to operating outside of well-defined geographical and service boundaries.

Overall, the disruption in the taxi industry is only in its initial phases. In the initial euphoric phase, ridesharing will expand coverage, reduce travelling costs and improve service quality. But as competition takes its toll, traditional taxi and public transit coverage may be cut. The fall-out may leave huge gaps in affordable service availability or may be detrimental to the welfare of drivers in the future.

1 thought on “The sharing economy: Disruptive effects of ridesharing”

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Organisation of households: Household formation and the housing market

Phuah Eng Chye

I was formerly a securities regulator and equities analyst. I started writing these articles (and a book) because I felt that there were a lot of economic theories that didn’t seem to match up to the realities we are facing. This also means that a lot of policies (based on these theories) are wrong. So I’ve tried to make sense of how things worked based on the paradigm of an information society. Its a challenging topic and difficult to pin down. This means I have had to explore issues over a wide range of policy areas. Over the next few months, I will cover the service economy, the sharing economy, household and work structures before moving onto policy issues on the anorexic economy (role of corporates, basic income, housing affordability) and the financialisation process (capital, monetary policy, securities regulation).